Overview

Dataset statistics

Number of variables11
Number of observations5788
Missing cells5788
Missing cells (%)9.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory525.8 KiB
Average record size in memory93.0 B

Variable types

Categorical3
Numeric4
Text3
Unsupported1

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15246/A/1/datasetView.do

Alerts

대여일자 has constant value ""Constant
대여구분코드 has constant value ""Constant
이용건수 is highly overall correlated with 이동거리(M) and 1 other fieldsHigh correlation
이동거리(M) is highly overall correlated with 이용건수 and 1 other fieldsHigh correlation
이용시간(분) is highly overall correlated with 이용건수 and 1 other fieldsHigh correlation
성별 has 5788 (100.0%) missing valuesMissing
성별 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-18 04:55:05.423347
Analysis finished2024-05-18 04:55:12.271935
Duration6.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대여일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size45.3 KiB
2022-07-01
5788 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-07-01
2nd row2022-07-01
3rd row2022-07-01
4th row2022-07-01
5th row2022-07-01

Common Values

ValueCountFrequency (%)
2022-07-01 5788
100.0%

Length

2024-05-18T13:55:12.478415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:55:12.900844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-07-01 5788
100.0%

대여소번호
Real number (ℝ)

Distinct2459
Distinct (%)42.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2053.1881
Minimum102
Maximum5855
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size51.0 KiB
2024-05-18T13:55:13.404668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum102
5-th percentile252
Q1844.75
median1685
Q33204
95-th percentile4684
Maximum5855
Range5753
Interquartile range (IQR)2359.25

Descriptive statistics

Standard deviation1438.257
Coefficient of variation (CV)0.70049937
Kurtosis-0.85400368
Mean2053.1881
Median Absolute Deviation (MAD)968
Skewness0.58118333
Sum11883853
Variance2068583.2
MonotonicityNot monotonic
2024-05-18T13:55:13.939014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1293 7
 
0.1%
1661 6
 
0.1%
1026 6
 
0.1%
1662 5
 
0.1%
1449 5
 
0.1%
648 5
 
0.1%
113 5
 
0.1%
1668 5
 
0.1%
3421 5
 
0.1%
731 5
 
0.1%
Other values (2449) 5734
99.1%
ValueCountFrequency (%)
102 2
< 0.1%
103 2
< 0.1%
104 2
< 0.1%
105 2
< 0.1%
106 2
< 0.1%
107 3
0.1%
108 4
0.1%
109 2
< 0.1%
111 1
 
< 0.1%
112 2
< 0.1%
ValueCountFrequency (%)
5855 2
< 0.1%
5854 2
< 0.1%
5853 3
0.1%
5851 2
< 0.1%
5753 2
< 0.1%
5752 3
0.1%
5306 3
0.1%
5305 1
 
< 0.1%
5301 3
0.1%
5082 3
0.1%

대여소
Text

Distinct2459
Distinct (%)42.5%
Missing0
Missing (%)0.0%
Memory size45.3 KiB
2024-05-18T13:55:14.513244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length31
Mean length15.618003
Min length7

Characters and Unicode

Total characters90397
Distinct characters575
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique439 ?
Unique (%)7.6%

Sample

1st row731. 서울시 도로환경관리센터
2nd row733. 신정이펜하우스314동
3rd row734. 신트리공원 입구
4th row735. 영도초등학교
5th row739. 신월사거리
ValueCountFrequency (%)
앞 1501
 
8.8%
출구 253
 
1.5%
옆 216
 
1.3%
1번출구 168
 
1.0%
교차로 152
 
0.9%
사거리 142
 
0.8%
입구 126
 
0.7%
3번출구 122
 
0.7%
뒤 114
 
0.7%
2번출구 104
 
0.6%
Other values (4916) 14175
83.0%
2024-05-18T13:55:15.445445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11388
 
12.6%
. 5808
 
6.4%
1 4599
 
5.1%
2 3437
 
3.8%
3 2821
 
3.1%
4 2726
 
3.0%
5 2158
 
2.4%
0 2073
 
2.3%
6 1999
 
2.2%
구 1889
 
2.1%
Other values (565) 51499
57.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 46531
51.5%
Decimal Number 24778
27.4%
Space Separator 11388
 
12.6%
Other Punctuation 5884
 
6.5%
Uppercase Letter 686
 
0.8%
Close Punctuation 491
 
0.5%
Open Punctuation 491
 
0.5%
Lowercase Letter 86
 
0.1%
Dash Punctuation 43
 
< 0.1%
Math Symbol 7
 
< 0.1%
Other values (3) 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1889
 
4.1%
앞 1754
 
3.8%
역 1468
 
3.2%
번 1302
 
2.8%
동 1275
 
2.7%
출 1272
 
2.7%
교 920
 
2.0%
파 845
 
1.8%
아 813
 
1.7%
리 803
 
1.7%
Other values (504) 34190
73.5%
Uppercase Letter
ValueCountFrequency (%)
S 91
13.3%
K 73
10.6%
T 63
 
9.2%
C 61
 
8.9%
A 54
 
7.9%
D 44
 
6.4%
B 37
 
5.4%
G 37
 
5.4%
P 35
 
5.1%
M 32
 
4.7%
Other values (13) 159
23.2%
Lowercase Letter
ValueCountFrequency (%)
e 29
33.7%
k 14
16.3%
s 14
16.3%
n 8
 
9.3%
y 4
 
4.7%
l 4
 
4.7%
t 3
 
3.5%
f 2
 
2.3%
r 2
 
2.3%
h 2
 
2.3%
Other values (3) 4
 
4.7%
Decimal Number
ValueCountFrequency (%)
1 4599
18.6%
2 3437
13.9%
3 2821
11.4%
4 2726
11.0%
5 2158
8.7%
0 2073
8.4%
6 1999
8.1%
7 1874
7.6%
8 1656
 
6.7%
9 1435
 
5.8%
Other Punctuation
ValueCountFrequency (%)
. 5808
98.7%
, 46
 
0.8%
& 16
 
0.3%
· 8
 
0.1%
? 6
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 4
57.1%
+ 3
42.9%
Other Number
ValueCountFrequency (%)
① 3
60.0%
② 2
40.0%
Space Separator
ValueCountFrequency (%)
11388
100.0%
Close Punctuation
ValueCountFrequency (%)
) 491
100.0%
Open Punctuation
ValueCountFrequency (%)
( 491
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 43
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 46534
51.5%
Common 43091
47.7%
Latin 772
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1889
 
4.1%
앞 1754
 
3.8%
역 1468
 
3.2%
번 1302
 
2.8%
동 1275
 
2.7%
출 1272
 
2.7%
교 920
 
2.0%
파 845
 
1.8%
아 813
 
1.7%
리 803
 
1.7%
Other values (505) 34193
73.5%
Latin
ValueCountFrequency (%)
S 91
 
11.8%
K 73
 
9.5%
T 63
 
8.2%
C 61
 
7.9%
A 54
 
7.0%
D 44
 
5.7%
B 37
 
4.8%
G 37
 
4.8%
P 35
 
4.5%
M 32
 
4.1%
Other values (26) 245
31.7%
Common
ValueCountFrequency (%)
11388
26.4%
. 5808
13.5%
1 4599
10.7%
2 3437
 
8.0%
3 2821
 
6.5%
4 2726
 
6.3%
5 2158
 
5.0%
0 2073
 
4.8%
6 1999
 
4.6%
7 1874
 
4.3%
Other values (14) 4208
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 46531
51.5%
ASCII 43850
48.5%
None 11
 
< 0.1%
Enclosed Alphanum 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11388
26.0%
. 5808
13.2%
1 4599
10.5%
2 3437
 
7.8%
3 2821
 
6.4%
4 2726
 
6.2%
5 2158
 
4.9%
0 2073
 
4.7%
6 1999
 
4.6%
7 1874
 
4.3%
Other values (47) 4967
11.3%
Hangul
ValueCountFrequency (%)
구 1889
 
4.1%
앞 1754
 
3.8%
역 1468
 
3.2%
번 1302
 
2.8%
동 1275
 
2.7%
출 1272
 
2.7%
교 920
 
2.0%
파 845
 
1.8%
아 813
 
1.7%
리 803
 
1.7%
Other values (504) 34190
73.5%
None
ValueCountFrequency (%)
· 8
72.7%
㈜ 3
 
27.3%
Enclosed Alphanum
ValueCountFrequency (%)
① 3
60.0%
② 2
40.0%

대여구분코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size45.3 KiB
정기권
5788 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row정기권
2nd row정기권
3rd row정기권
4th row정기권
5th row정기권

Common Values

ValueCountFrequency (%)
정기권 5788
100.0%

Length

2024-05-18T13:55:15.864456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:55:16.127743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기권 5788
100.0%

성별
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5788
Missing (%)100.0%
Memory size51.0 KiB

연령대
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size45.3 KiB
20대
2543 
30대
2164 
~10대
582 
40대
499 

Length

Max length4
Median length3
Mean length3.1005529
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row~10대
2nd row~10대
3rd row~10대
4th row~10대
5th row~10대

Common Values

ValueCountFrequency (%)
20대 2543
43.9%
30대 2164
37.4%
~10대 582
 
10.1%
40대 499
 
8.6%

Length

2024-05-18T13:55:16.396142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:55:16.652611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20대 2543
43.9%
30대 2164
37.4%
10대 582
 
10.1%
40대 499
 
8.6%

이용건수
Real number (ℝ)

HIGH CORRELATION 

Distinct43
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.101935
Minimum1
Maximum80
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size51.0 KiB
2024-05-18T13:55:17.003115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q35
95-th percentile13
Maximum80
Range79
Interquartile range (IQR)4

Descriptive statistics

Standard deviation4.6619961
Coefficient of variation (CV)1.1365358
Kurtosis25.570753
Mean4.101935
Median Absolute Deviation (MAD)1
Skewness3.624909
Sum23742
Variance21.734207
MonotonicityNot monotonic
2024-05-18T13:55:17.310732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
1 1926
33.3%
2 1007
17.4%
3 673
 
11.6%
4 475
 
8.2%
5 362
 
6.3%
6 269
 
4.6%
7 236
 
4.1%
8 173
 
3.0%
9 126
 
2.2%
10 107
 
1.8%
Other values (33) 434
 
7.5%
ValueCountFrequency (%)
1 1926
33.3%
2 1007
17.4%
3 673
 
11.6%
4 475
 
8.2%
5 362
 
6.3%
6 269
 
4.6%
7 236
 
4.1%
8 173
 
3.0%
9 126
 
2.2%
10 107
 
1.8%
ValueCountFrequency (%)
80 1
 
< 0.1%
55 1
 
< 0.1%
48 1
 
< 0.1%
45 1
 
< 0.1%
42 1
 
< 0.1%
40 1
 
< 0.1%
39 1
 
< 0.1%
38 1
 
< 0.1%
35 2
< 0.1%
34 3
0.1%

운동량
Text

Distinct5249
Distinct (%)90.7%
Missing0
Missing (%)0.0%
Memory size45.3 KiB
2024-05-18T13:55:17.944890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.5378369
Min length2

Characters and Unicode

Total characters32053
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4820 ?
Unique (%)83.3%

Sample

1st row53.63
2nd row25.06
3rd row368.82
4th row57.64
5th row73.58
ValueCountFrequency (%)
0.00 30
 
0.5%
n 9
 
0.2%
23.17 7
 
0.1%
73.10 5
 
0.1%
14.26 5
 
0.1%
40.91 4
 
0.1%
10.26 4
 
0.1%
93.00 4
 
0.1%
21.36 4
 
0.1%
13.90 4
 
0.1%
Other values (5239) 5712
98.7%
2024-05-18T13:55:19.118128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 5779
18.0%
1 3788
11.8%
2 3279
10.2%
3 2835
8.8%
4 2575
8.0%
5 2369
7.4%
7 2334
7.3%
8 2296
 
7.2%
0 2292
 
7.2%
6 2291
 
7.1%
Other values (3) 2215
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 26256
81.9%
Other Punctuation 5788
 
18.1%
Uppercase Letter 9
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3788
14.4%
2 3279
12.5%
3 2835
10.8%
4 2575
9.8%
5 2369
9.0%
7 2334
8.9%
8 2296
8.7%
0 2292
8.7%
6 2291
8.7%
9 2197
8.4%
Other Punctuation
ValueCountFrequency (%)
. 5779
99.8%
\ 9
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
N 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 32044
> 99.9%
Latin 9
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 5779
18.0%
1 3788
11.8%
2 3279
10.2%
3 2835
8.8%
4 2575
8.0%
5 2369
7.4%
7 2334
7.3%
8 2296
 
7.2%
0 2292
 
7.2%
6 2291
 
7.1%
Other values (2) 2206
 
6.9%
Latin
ValueCountFrequency (%)
N 9
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32053
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 5779
18.0%
1 3788
11.8%
2 3279
10.2%
3 2835
8.8%
4 2575
8.0%
5 2369
7.4%
7 2334
7.3%
8 2296
 
7.2%
0 2292
 
7.2%
6 2291
 
7.1%
Other values (3) 2215
 
6.9%

탄소량
Text

Distinct784
Distinct (%)13.5%
Missing0
Missing (%)0.0%
Memory size45.3 KiB
2024-05-18T13:55:19.884117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.0067381
Min length2

Characters and Unicode

Total characters23191
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique250 ?
Unique (%)4.3%

Sample

1st row0.50
2nd row0.23
3rd row3.02
4th row0.50
5th row0.69
ValueCountFrequency (%)
0.26 57
 
1.0%
0.29 53
 
0.9%
0.22 51
 
0.9%
0.19 50
 
0.9%
0.13 48
 
0.8%
0.23 48
 
0.8%
0.35 45
 
0.8%
0.24 45
 
0.8%
0.21 45
 
0.8%
0.18 44
 
0.8%
Other values (774) 5302
91.6%
2024-05-18T13:55:21.107188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 5779
24.9%
0 3912
16.9%
1 2615
11.3%
2 2099
 
9.1%
3 1650
 
7.1%
4 1367
 
5.9%
5 1335
 
5.8%
6 1197
 
5.2%
8 1095
 
4.7%
7 1066
 
4.6%
Other values (3) 1076
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17394
75.0%
Other Punctuation 5788
 
25.0%
Uppercase Letter 9
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3912
22.5%
1 2615
15.0%
2 2099
12.1%
3 1650
9.5%
4 1367
 
7.9%
5 1335
 
7.7%
6 1197
 
6.9%
8 1095
 
6.3%
7 1066
 
6.1%
9 1058
 
6.1%
Other Punctuation
ValueCountFrequency (%)
. 5779
99.8%
\ 9
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
N 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23182
> 99.9%
Latin 9
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 5779
24.9%
0 3912
16.9%
1 2615
11.3%
2 2099
 
9.1%
3 1650
 
7.1%
4 1367
 
5.9%
5 1335
 
5.8%
6 1197
 
5.2%
8 1095
 
4.7%
7 1066
 
4.6%
Other values (2) 1067
 
4.6%
Latin
ValueCountFrequency (%)
N 9
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23191
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 5779
24.9%
0 3912
16.9%
1 2615
11.3%
2 2099
 
9.1%
3 1650
 
7.1%
4 1367
 
5.9%
5 1335
 
5.8%
6 1197
 
5.2%
8 1095
 
4.7%
7 1066
 
4.6%
Other values (3) 1076
 
4.6%

이동거리(M)
Real number (ℝ)

HIGH CORRELATION 

Distinct5055
Distinct (%)87.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7643.8701
Minimum0
Maximum107244.06
Zeros34
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size51.0 KiB
2024-05-18T13:55:21.545071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile604.273
Q11873.9225
median4513.395
Q310117.03
95-th percentile25178.57
Maximum107244.06
Range107244.06
Interquartile range (IQR)8243.1075

Descriptive statistics

Standard deviation8972.4594
Coefficient of variation (CV)1.1738111
Kurtosis12.450783
Mean7643.8701
Median Absolute Deviation (MAD)3203.11
Skewness2.7997009
Sum44242720
Variance80505027
MonotonicityNot monotonic
2024-05-18T13:55:21.985266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 34
 
0.6%
1230.0 12
 
0.2%
1640.0 9
 
0.2%
1240.0 9
 
0.2%
1010.0 9
 
0.2%
1490.0 8
 
0.1%
530.0 8
 
0.1%
1120.0 8
 
0.1%
900.0 8
 
0.1%
1590.0 8
 
0.1%
Other values (5045) 5675
98.0%
ValueCountFrequency (%)
0.0 34
0.6%
0.1 1
 
< 0.1%
0.13 1
 
< 0.1%
0.2 1
 
< 0.1%
0.29 1
 
< 0.1%
8.61 1
 
< 0.1%
11.26 1
 
< 0.1%
17.09 1
 
< 0.1%
20.0 1
 
< 0.1%
26.45 1
 
< 0.1%
ValueCountFrequency (%)
107244.06 1
< 0.1%
102592.22 1
< 0.1%
79340.08 1
< 0.1%
73013.66 1
< 0.1%
70375.72 1
< 0.1%
66753.88 1
< 0.1%
65945.0 1
< 0.1%
60508.79 1
< 0.1%
60460.37 1
< 0.1%
59406.64 1
< 0.1%

이용시간(분)
Real number (ℝ)

HIGH CORRELATION 

Distinct351
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60.435384
Minimum0
Maximum945
Zeros3
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size51.0 KiB
2024-05-18T13:55:22.407661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q114
median36
Q378
95-th percentile204
Maximum945
Range945
Interquartile range (IQR)64

Descriptive statistics

Standard deviation72.82399
Coefficient of variation (CV)1.2049893
Kurtosis14.707915
Mean60.435384
Median Absolute Deviation (MAD)26
Skewness2.9765428
Sum349800
Variance5303.3335
MonotonicityNot monotonic
2024-05-18T13:55:22.824093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 145
 
2.5%
5 142
 
2.5%
7 132
 
2.3%
6 132
 
2.3%
9 123
 
2.1%
8 121
 
2.1%
3 111
 
1.9%
10 108
 
1.9%
15 104
 
1.8%
11 104
 
1.8%
Other values (341) 4566
78.9%
ValueCountFrequency (%)
0 3
 
0.1%
1 24
 
0.4%
2 71
1.2%
3 111
1.9%
4 145
2.5%
5 142
2.5%
6 132
2.3%
7 132
2.3%
8 121
2.1%
9 123
2.1%
ValueCountFrequency (%)
945 1
< 0.1%
819 1
< 0.1%
679 1
< 0.1%
618 1
< 0.1%
581 1
< 0.1%
575 1
< 0.1%
561 1
< 0.1%
557 1
< 0.1%
554 1
< 0.1%
546 1
< 0.1%

Interactions

2024-05-18T13:55:10.376088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:06.873807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:07.929294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:09.207157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:10.665977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:07.135874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:08.396595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:09.476280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:10.946602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:07.413996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:08.677374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:09.766944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:11.211923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:07.674207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:08.946467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:10.100791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T13:55:23.094543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호연령대이용건수이동거리(M)이용시간(분)
대여소번호1.0000.1770.0910.0630.076
연령대0.1771.0000.3110.2470.243
이용건수0.0910.3111.0000.8340.885
이동거리(M)0.0630.2470.8341.0000.892
이용시간(분)0.0760.2430.8850.8921.000
2024-05-18T13:55:23.376704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호이용건수이동거리(M)이용시간(분)연령대
대여소번호1.000-0.058-0.052-0.0740.107
이용건수-0.0581.0000.8330.8320.143
이동거리(M)-0.0520.8331.0000.9300.160
이용시간(분)-0.0740.8320.9301.0000.148
연령대0.1070.1430.1600.1481.000

Missing values

2024-05-18T13:55:11.586265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T13:55:12.056305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

대여일자대여소번호대여소대여구분코드성별연령대이용건수운동량탄소량이동거리(M)이용시간(분)
02022-07-01731731. 서울시 도로환경관리센터정기권<NA>~10대253.630.502150.020
12022-07-01733733. 신정이펜하우스314동정기권<NA>~10대125.060.231004.35
22022-07-01734734. 신트리공원 입구정기권<NA>~10대2368.823.0213032.2875
32022-07-01735735. 영도초등학교정기권<NA>~10대257.640.502173.0821
42022-07-01739739. 신월사거리정기권<NA>~10대373.580.692940.015
52022-07-01742742. 등촌역 5번 출구 뒤정기권<NA>~10대173.100.662840.016
62022-07-01745745. 강서초등학교정기권<NA>~10대132.870.391660.015
72022-07-01746746. 목동2단지 상가정기권<NA>~10대4294.402.5410966.8971
82022-07-01505505. 자양사거리 광진아크로텔 앞정기권<NA>~10대2100.571.024397.3630
92022-07-01942942. 상림마을 생태공원정기권<NA>~10대112.270.13563.463
대여일자대여소번호대여소대여구분코드성별연령대이용건수운동량탄소량이동거리(M)이용시간(분)
57782022-07-0134163416.동묘앞역 6번출구정기권<NA>40대264.610.552373.4822
57792022-07-0134173417.창신3동주민센터정기권<NA>40대147.050.421827.7215
57802022-07-0134213421.혜화역 1번출구정기권<NA>40대4182.251.657084.2490
57812022-07-01369369. 광화문 시민열린마당정기권<NA>40대6210.861.898082.98119
57822022-07-0134233423.현대그룹(본사)정기권<NA>40대163.840.582480.020
57832022-07-0134273427.인왕산 아이파크 정문정기권<NA>40대1105.280.954089.9821
57842022-07-01348348. 독립문역 사거리정기권<NA>40대138.220.261135.625
57852022-07-0110701070.(시립)고덕평생학습관정기권<NA>40대131.270.351490.012
57862022-07-0110721072.고덕역 5번출구정기권<NA>40대161.290.602579.7219
57872022-07-0110731073. SSTS 몰 앞정기권<NA>40대156.670.371590.016